Hi. I’m Professor of Politics and Affiliated Professor of Law at New York University, and Director of the Public Safety Lab. I have served as Chair of NYU’s Department of Politics and as Interim Dean of NYU’s Graduate School of Arts and Science.

My CV can be downloaded here. My email is anna [dot] harvey [at] nyu. My mailing address is Department of Politics, New York University, 19 W. 4th St., New York, NY 10012. My office number is 308.

I founded the Public Safety Lab in June 2017 to provide data science and social science support to communities and law enforcement agencies seeking to modernize and improve their criminal justice practices. For example, many relatively minor offenses are easy to detect and interdict. Many more serious offenses are much harder to detect and interdict. We may then overpunish relatively minor offenses, and underpunish more serious offenses. The Public Safety Lab works with communities and law enforcement agencies to achieve more productive allocations of public safety resources.

We are currently working with several jurisdictions on projects that include: estimating the effect of financial incentives on traffic safety enforcement; estimating the effects on recidivism of the duration of pretrial detention in over 1,000 largely rural county jails; estimating the effects on recidivism of the use of prosecutorial discretion to reduce prosecutions for minor offenses; estimating the effects of New York State intermediate appellate judge reelection and reappointment calendars on rulings in criminal appeals; estimating the effects of assigning 911 calls involving mental health and substance abuse issues to medical response teams as opposed to law enforcement response teams; estimating the presence of racial bias in 911 call response; developing a randomized controlled trial of a platform that pushes an SMS-based survey to 911 callers, asking them to rate their experience of the police response; and estimating the effects of urban school district calendars on the risk of sex trafficking of high school-age girls.

In the first paper to come out of my Public Safety Lab work, joint with Greg DeAngelo (Economics, Claremont Graduate University) and Murat Mungan (Law, George Mason University), we address concerns about “policing for profit,” or the deployment of law enforcement resources to raise funds for cash-strapped jurisdictions. Identifying the causal effect of fiscal incentives on law enforcement behavior has remained elusive. Researchers have given little theoretical attention to the potentially confounding responses of potential offenders to increased revenue-seeking by law enforcers. Moreover, empirical designs have not effectively addressed the endogeneity of the spatial and temporal variation in fiscal incentives to factors that may directly affect law enforcement or offender behavior. We model the effects of fiscal incentives on traffic safety enforcement, finding that rules allocating a greater share of fine revenues to deploying jurisdictions may induce increased enforcement effort by patrol officers, and consequent reductions in unsafe driving behavior, with only indeterminate effects on the frequency of citations. We test this model using citation and accident data from Saskatchewan, Canada between 1995 and 2017, for towns policed under the province’s contract with the Royal Canadian Mounted Police. We find that fiscal rules reducing the share of fine revenue captured by the province in towns above a sharply defined population threshold increase the frequency and severity of accidents in these towns, but have no effects on the frequency of traffic stops. We also find that cited drivers in towns just below this threshold are given fewer days to pay their fines and incur higher late fines as a percentage of assessed fines. These results are robust to the use of both data-driven regression discontinuity and local randomization inference strategies. We observe no discontinuities in the citation and accident data at the threshold during the period prior to the introduction of these fiscal rules, in the areas “near” these jurisdictions, within which the province receives 100% of fine revenue throughout our period of interest, or at any of 12 placebo thresholds constructed on either side of the actual population threshold.

Several recent papers have used the as-if random assignment of bail judges to cases to estimate the effect of bail conditions on pretrial detention, and then the instrumented effect of pretrial detention on recidivism. These papers have reported compelling evidence that pretrial detention increases reoffending, most likely through some combination of the economic and social disruption and peer effects resulting from detention. However, these studies have all used case data from the same small number of large urban jurisdictions that can support the empirical strategy of as-if random assignment of bail judges to cases. Very little is known about the vast majority of pretrial detainees being held in largely rural and less populated county jails. Over 1,000 of these jails post their daily jail rosters online. Through the Public Safety Lab’s Jail Data Initiative, made possible by the generous support of the Laura and John Arnold Foundation, we are crawling these daily rosters and creating a defendant- and jail-level dataset on pretrial detention in these counties. We are also searching for counties that provide online access to criminal case and incarceration records, crawling these records, and merging them at the defendant level with the crawled jail rosters. Using these data, along with daily variation in jail capacity as an instrument, we will estimate the effects of pretrial detention on outcomes across a much broader range of jurisdictions than has previously been possible.

In the Public Safety Lab’s Prosecutorial Reform Initiative, we are working with several large urban and suburban district attorney offices to evaluate the effects of these offices’ recent reforms directed at reducing prosecutions for subfelony offenders. These reforms include strategies such as declining to prosecute, diversion, or issuing criminal summonses in lieu of prosecution for a range of subfelony offenses. While these reforms can dramatically reduce prosecutorial workloads, questions remain about their effects on offender behavior. Do offenders subject to these policy reforms reoffend more often, and/or escalate to more serious offending, as a consequence of the reduced threat of punishment for offending? Or do they reoffend less often, and/or deescalate repeat offending, as a consequence of the reduced disruption of their work and family lives enabled by the reforms? Using both a series of temporal and geographic discontinuities created by the reforms’ implementation, as well as the as-if random assignment of assistant district attorneys to subfelony cases, we are pursuing answers to these questions.

Another Public Safety Lab project involves assessing whether appellate judges treat some criminal defendants differently as a function of their retention calendars. Previous work has been limited to looking at judges (typically trial judges) who are either elected or appointed, and to drawing inferences across these different judges about the relative effects of election and appointment on outcomes. In this project, we look at New York State’s intermediate appellate judges, who are both elected and appointed (they must be elected, and repeatedly reelected, to be eligible to be appointed, and then repeatedly reappointed, by the state’s governor). Using structured data extracted from the crawled corpus of New York State intermediate appellate division rulings on criminal appeals between 2003 and 2017, merged with appellate judge election and appointment data, we are analyzing the within-judge effects of both reelection and reappointment on appellate rulings. Further, using information on defendant race, gender, and offense and incarceration histories extracted from the crawled corpus of New York State’s Department of Corrections records of state prison inmates, matched to the defendants in the appellate opinions, we are estimating whether reelection and/or reappointment effects vary as a function of defendant demographic and offense characteristics.

In two Public Safety Lab projects on 911 calls, we are looking at the process by which 911 calls are first triaged into medical or law enforcement responses, and then are further assigned call and priority codes by 911 call takers. These initial discretionary decisions made by call takers may have large impacts on outcomes. They may also be inflected by call taker biases that are activated by information reported by callers. Working with several large urban jurisdictions, we are sourcing several years of the original audio files of 911 callers and call takers, records of call takers’ coding decisions, Computer Assisted Dispatch records of the responses to calls, and Record Management System records of call outcomes. Using the as-if random assignment of calls to call takers, we are initially investigating three questions: 1) what is the effect of a medical response, relative to a law enforcement response, on call outcomes involving mental health and/or substance abuse issues? 2) conditional on assignment to a law enforcement response, what is the effect of call assignment to officers who have received Crisis Intervention Training (CIT) on call outcomes involving mental health/substance abuse issues? 3)  is there any evidence of racial bias in the handling of 911 calls by call takers, and if so, what effects does that bias have on call outcomes? 

In a related Public Safety Lab project, we are conducting a field experiment of a platform that sends a one-question text survey to 911 callers whose call has been answered by a large urban policing agency. The goal of the project is to assess whether providing an opportunity for those who interact with law enforcement to provide feedback on their experience can move both civilian and officer behavior in a more constructive direction. The text survey asks callers to report a rating between 1-10 for how they feel they were treated by responding officers. If a caller responds to the survey, she is sent a follow-up link to a longer survey asking for more detailed feedback on the agency’s response. Patrol officers are given access to an online dashboard reporting not only the average survey ratings for calls to which they responded, but also average survey ratings for other officers in their unit. In the field experiment, we are manipulating several aspects of the platform, and using both survey and administrative data to estimate treatment effects. For example, we are estimating the effect of receiving the text survey on caller behavior, using administrative records of subsequent calls from that phone number. We are also estimating the effect on officer behavior of receiving access to the survey ratings, using both pre- and post-treatment survey ratings and administrative records of the calls to which an officer responds. 

In another project from the Public Safety Lab, we are using data science tools to try to identify the presence of sex trafficking in online ads for and reviews of sex providers. We are first extracting structured data from the texts of the very large corpus of online sex ads and reviews of sex providers posted between 2010 and 2017, merging that structured data with information on sex trafficking investigations sourced from law enforcement agencies, and looking for features of ads that are predictive of the likely presence of sex trafficking. We are also looking for telephone numbers in online sex ads that are systematically more likely to be posted on days when high school-aged girls are out of school, but adults are typically at work (e.g., teacher “planning days”). Our working hypothesis is that these ads are likely to be posted by or on behalf of minor girls, potentially by traffickers. Using these ads as “ground truth,” we are then looking to identify features of these ads that can be used to predict the presence of potentially trafficked minor girls in the full corpus of ads and reviews.

In my non-Public Safety Lab work I am currently co-authoring a casebook on judicial decisionmaking (appropriately entitled, Judicial Decisionmaking (West Publishing, 2019)) with Andrew Martin (Michigan), Tom Clark (Emory), Maggie Lemos (Duke Law), Allison Larsen (William and Mary Law), and Barry Friedman (NYU Law). The casebook integrates both social science and legal approaches to understanding how judges decide cases.

Another current project, joint with Emily A. West (Political Science, University of Pittsburgh), investigates discrimination in public accommodations. Identification difficulties have to date precluded the estimation of causal effects from statutes prohibiting discrimination in public accommodations. We leverage the U.S. Supreme Court’s 1883 strike of the public accommodations provisions in the Civil Rights Act of 1875, along with ex ante variation in state-level statutes, to identify the impact of a federal statute protecting access to public accommodations. Using repeated geo-located medical exams of Union Army and U.S. Colored Troops veterans, and a series of geographic regression discontinuity and placebo designs, we find that the Court’s ruling led to large relative weight losses for USCT veterans in states without state-level public accommodation statutes. These findings suggest that, despite popular skepticism about the importance of discrimination in public accommodations, this form of discrimination in fact has material negative impacts on the well-being of its victims, and that statutes prohibiting such discrimination can mitigate these impacts.

A third project investigates the causal impact of money in elections. One article in this project uses the Supreme Court’s ruling in Buckley v. Valeo (1976) to identify the causal impact of removing state limits on campaign spending. The Supreme Court’s campaign finance jurisprudence rests on a distinction between spending restrictions (generally struck) and contribution restrictions (often upheld). In Buckley v. Valeo (1976), the case originating this distinction, the majority rejected an “anti-distortion” rationale for spending restrictions, claiming that campaign spending is merely an effect of candidate support, not a cause of candidate support. If this claim is true, then removing restrictions on campaign spending should have no discernible causal impacts. This article tests the Buckley majority’s empirical claim using its own ruling, which struck limits on campaign spending in state elections in 26 states. Estimates consistently suggest that the Buckley-induced removal of state limits on campaign spending led to increased Republican voteshares, increased Republican candidate entry, and decreased Democratic candidate entry in state legislative and gubernatorial elections in states affected by the ruling, and to both increased Republican House voteshares and the election of more conservative freshman Republican House incumbents in states both affected by the ruling and holding concurrent federal and state elections. These findings suggest that the rationale for the core distinction in the Supreme Court’s campaign finance jurisprudence has little empirical foundation.

Another campaign finance paper, joint with Taylor Mattia (PhD student, NYU Department of Politics), looks at the causal impact of Citizens United v. FEC (2010) on legislators’ preferences. Recent work has suggested that the Supreme Court’s ruling in Citizens United (2010), eliminating restrictions on independent spending in elections, increased the probability of election of Republican state legislative candidates (Klumpp et al 2016). Left unexplored has been whether the Court’s ruling in Citizens United not only increased the number of Republican state legislators, but also induced the movement of state legislators’ preferences in a more conservative direction, net of any effects on Republican candidates’ probabilities of election. We attempt to distinguish these electoral and preference effects of Citizens United. Estimates consistently suggest that the Citizens United-induced removal of state restrictions on independent spending led not only to increased probabilities of election for Republican state legislative candidates, but also to larger within-district increases in the conservatism of state legislators’ preferences in formerly Democratic districts electing Republican state legislators post-ruling. These estimates, which are robust to a series of matching and placebo exercises, may provide support for the claim that an increased presence of money in elections has contributed to the increased conservatism of Republican elected officials.

Several of these projects involve applying the tools of causal inference to historical data. In a paper joint with Greg DeAngelo (Economics, Claremont Graduate University), prepared for a special issue of Public Choice on Causal Inference and American Political Development, we explore the application of regression discontinuity (RD) designs to three questions of interest to researchers in the subfield of American political development (APD). APD scholars have long been interested in questions related to the development of “state capacity” in the United States, or the growth of a salaried and merit-based federal bureaucracy capable of competently administering programs of social provision. We illustrate how RD designs can be used to investigate the impacts of the relative absence of federal state capacity during the 19th century; of the subsequent growth of a professional salaried civil service around the turn of the 20th century and beyond; and of the resulting growth of the presence of the administrative state in Americans’ daily lives. We first illustrate the use of a geographic RD design to estimate the causal impacts of a Reconstruction-era federal civil rights statute during the period prior to the development of significant federal state capacity. Second, we explore the possible causes of the late 19th century decline in the use of monetary rewards to motivate civil servants through the use of a population-based RD design to estimate the causal impacts of financial incentives on law enforcement effort and civilian compliance. Third, we illustrate an opportunity to test claims about the impacts of the growth of the “carceral state” through the use of a modified resource constraint RD design to estimate the causal impacts of police deployments on a variety of outcomes.

In The Civil Rights Cases (1883), Buckley v. Valeo (1976), and Citizens United (2010), unelected judges struck federal statutes enacted by legislative majorities; legislative supermajorities are required to overturn these rulings. In another project I investigate the historical origins of this form of “entrenched” judicial review. Among those current democracies that were former colonies, the presence of entrenched judicial review is strongly associated with pre-colonial histories of marked inequality, a finding consistent with the hypothesis that entrenched judicial review was adopted at least in part to preserve pre-colonial inequality from legislative redistribution.

Yet unelected judges are not necessarily unresponsive to legislative preferences. In the U.S., federal judges serve only on the condition of good behavior, and congressional majorities control judicial salaries, budgets, and jurisdiction. In A Mere Machine: The Supreme Court, Congress, and American Democracy (Yale University Press, 2013), I reported evidence indicating that, even in constitutional cases, the U.S. Supreme Court defers to congressional preferences, in particular to the preferences of majorities in the House of Representatives (the chamber that originates both impeachment and appropriations actions). To view an interview about A Mere Machine on CSPAN’s Book TV, click here.

In order to generate the findings reported in A Mere Machine, several methodological challenges had to be addressed. These challenges included constructing an objectively defined measure of the ideological direction of Supreme Court judgments, the initial work for which was done jointly with Michael J. Woodruff (former NYU Politics PhD student). They also included addressing the selection bias in the Court’s docket, the early work for which was done jointly with Barry Friedman (NYU Professor of Law) (here and here). Other work on the responsiveness of the Supreme Court to congressional preferences may be found here and here.

In earlier work I investigated the proposition that partisanship may be modeled as a social convention, providing social benefits to in-group members (and social penalties to out-group members). Electoral laws that make partisan acts more public (e.g. party registration) or less public (e.g. secret ballots; party primaries rather than caucuses) will then affect the ability of neighbors to coordinate on local party social conventions, a hypothesis for which there is empirical support.

This work on partisanship as a social convention grew out of my first major project, which investigated the competition to mobilize women’s votes after constitutional female suffrage. In Votes without Leverage: Women in American Electoral Politics, 1920-1970 (Cambridge University Press, Series on the Political Economy of Institutions and Decisions, 1998), I suggested that, if there is a significant social component to turnout and partisanship, then competition to mobilize votes through social networks will be much like competition to mobilize consumers of services offered through networks (e.g., telephone networks). Markets for networked services are generally marked by imperfect competition, with early entrants having significant advantages over later entrants. Likewise, the decision by the National League of Women Voters (the former female suffrage organization) in 1923 to cede the market in women’s votes to the party organizations may have followed from its necessarily late entry into this imperfectly competitive market. Votes Without Leverage built on articles published here and here. A post on Vox in honor of the 100th anniversary of Jeannette Rankin’s 1917 swearing-in as the first woman to join the House of Representatives may be found here.